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Genome-wide Association Studies-GWAS

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...

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Related Experiment Video

Updated: Mar 31, 2026

Infinium Assay for Large-scale SNP Genotyping Applications

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

Quality Control Procedures for High-Throughput Genetic Association Studies.

Ciara Coleman^1,2, Emma M Quinn^1,2, Ross McManus^3,4

¹Department of Medicine, Institute of Molecular Medicine, Trinity College Dublin, College Green, Dublin 2, Ireland.

Methods in Molecular Biology (Clifton, N.J.)

|October 27, 2015

Summary

Genome-wide association studies identified celiac disease (CD) risk variants. The Immunochip array offers high-density genotyping for deeper analysis of genetic factors in CD and other autoimmune diseases.

Keywords:

Celiac disease Genome-wide association study Immunochip

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Last Updated: Mar 31, 2026

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Published on: November 19, 2013

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Published on: November 3, 2010

Area of Science:

Genetics
Immunology
Bioinformatics

Background:

Genome-wide association (GWA) studies are crucial for identifying genetic disease determinants.
Early GWA studies identified celiac disease (CD) risk variants but lacked marker density.
The Immunochip array was developed for deep replication and fine mapping of autoimmune disease loci.

Purpose of the Study:

To describe methods for Immunochip genotyping.
To outline bioinformatics for quality control and analysis of Immunochip data.
To facilitate genetic analysis of celiac disease and other autoimmune conditions.

Main Methods:

Immunochip genotyping using a custom high-density array.
Bioinformatics pipelines for data quality control.
Statistical analysis of genetic polymorphism data.

Main Results:

The Immunochip array enables high-density genotyping for genetic studies.
Established methods for quality control and analysis of Immunochip data.
Facilitates comparison of genetic markers across multiple autoimmune diseases.

Conclusions:

Immunochip genotyping and bioinformatics are essential for detailed genetic analysis.
This approach enhances the study of genetic variance in celiac disease.
Provides a standardized platform for investigating autoimmune and inflammatory diseases.